Scooter-borne first responders could prove vital for emergency healthcare

Heart Rescue India, a partnership between Ramaiah Memorial Hospital and the US-based University of Illinois, has taken the help of Bengaluru-based AI startup Inkers.ai to put together such an emergency response protocol.Alnoor Peermohamed | ETtech | May 03, 2019, 06:09 IST

Imagine this — a team of scooter-borne first responders equipped with a smartphone and portable ECG machines are stationed nearby to reach within 10 minutes as soon as a person experiences a heart attack or stroke.

The emergency calls to a command centre are automatically directed to the responder who can reach the fastest. Complex routing algorithms using geo-location data and cell phone triangulation are fed into AI to select the quickest route. The ECG scan of the patient is then relayed to a team of experts at a hospital. If flagged as a heart attack or stroke, the system deploys an ambulance to collect the patient.

This emergency response protocol is vital, since there is a golden hour to administer treatment before the damage to the patient is irreparable or fatal. It is also a major issue for doctors in large metros where traffic snarls negate the presence of several high-quality cardiac care centres.

Heart Rescue India, a partnership between Ramaiah Memorial Hospital and the US-based University of Illinois, has taken the help of Bengaluru-based AI startup Inkers.ai to put together such an emergency response protocol.

Inkers, which works on facial recognition and machine vision, is building the technology backbone for Heart Rescue India, and the pilot is looking to address all incoming calls for heart attacks and strokes within a 10-km radius, potentially running into thousands of cases in a year.

Ramaiah Memorial Hospital has put together a hub and spoke model with six other hospitals in Bengaluru, including state-run Jayadeva Institute of Cadiovascular Sciences.

The model plans to reduce the time taken to respond, diagnose and administer preliminary treatment for patients with ST-Elevation Myocardial Infarction (STEMI) within 60-90 minutes of the emergency alert.

“Half of the patients who have a heart attack die before they reach a hospital. Even if a patient calls an ambulance, there’s no promise that they’d be taken to the right hospital,” says Aruna Ramesh, Head of Department for Emergency Medicine at Ramaiah Medical College and Programme Director for Heart Rescue India. “When it comes to your heart, time is life.”

While hospitals are getting sophisticated machines to diagnose and treat patients accurately, in the case of STEMI it is largely pre-hospital care that needs to be addressed. Further, in cities such as Bengaluru which suffer from traffic blocks, the right diagnosis before admission becomes critical.

The situation is especially alarming for India since cardiovascular diseases contribute 28.1 per cent of the total deaths in the country, according to a 2018 report by Lancet, up from 15.2% in 1990.

If all goes well, Ramesh says, the patient could be admitted within 60 minutes, permitting immediate treatment. In fact, Ramaiah Memorial Hospital and Heart Rescue India have been organising local awareness drives about heart disease as well as collecting information from high-risk patients.

Inkers, which is building the routing algorithm for the emergency responders, also plans to use AI-enabled cameras to identify the incoming patient and guide doctors on the mandatory steps needed for STEMI treatment.

“We’ll do a phased rollout of all the systems, which will include cameras with in-built AI that can watch the doctor administering care to a patient and guide them,” said Rohan Shravan, founder at Inkers.ai. “Today, this is done by a nurse, but hospitals have complained that they have a massive shortage of manpower.”

The system, however, still relies on people identifying the symptoms related to a heart attack. “Until artificial intelligence can tell you that you’re having a heart attack, we’re going to have to rely on human intelligence,” Ramesh says.

The pilot, which has taken years to build and train staff, will go live later this month, and the data will be used for better pre-hospital care in large cities and, potentially, across the world.

“The use case needs a lot of systems to talk to each other and if we want to hit our time targets for delivering care, we can’t rely on doing things manually like we’re used to today,” says Sharavan.